Digital Commons Network^™

Empirical Exploration Of Software Testing, Samia Alblwi

Dissertations

Despite several advances in software engineering research and development, the quality of software products remains a considerable challenge. For all its theoretical limitations, software testing remains the main method used in practice to control, enhance, and certify software quality. This doctoral work comprises several empirical studies aimed at analyzing and assessing common software testing approaches, methods, and assumptions. In particular, the concept of mutant subsumption is generalized by taking into account the possibility for a base program and its mutants to diverge for some inputs, demonstrating the impact of this generalization on how subsumption is defined. The problem of mutant …

Sustainable And Cost-Effective Work Zone Scheduling On Two-Lane Highways With Managed Lanes, Ahmed Z. Edrees

Dissertations

Roadway maintenance projects greatly influence the roadway capacity, resulting in potential traffic disturbances captured by delays. Additionally, costs associated with these projects tend to be exorbitantly extensive. Most agencies and planners try to find a solution that minimizes roadway maintenance costs, traffic delays, crash risks, and environmental impact.

Work zones on two-way two-lane roadway typically avoids high-demand periods. Lane-closure scenario is commonly used and converts the open lane into a phantom intersection, alternating two-direction movements on one lane with the help of a flagger or a temporary signal. Alternatively, using shoulders as temporarily managed lanes allows for simultaneous two-way movements …

Network Slicing And Noma Enabled Mobile Edge Computing For Next-Generation Networks, Mohammad Arif Hossain

Dissertations

The advent of next-generation wireless networks ushers in a new era of potential, harnessing cutting-edge technologies like mobile edge computing (MEC), non-orthogonal multiple access (NOMA), and network slicing as pivotal drivers of transformation. Within this landscape, an innovative approach is proposed by introducing a NOMA-enabled network slicing technique within MEC networks. This approach aims to achieve multiple objectives: meeting stringent quality of service requirements, minimizing service latency, and enhancing spectral efficiency. By seamlessly integrating NOMA with network slicing in edge computing environments, significant reductions in overall latency are achieved, alongside ensuring optimal resource allocation for NOMA users. To address these …

Integrating Laser Charging And Drones For Secure Edge Computing, Weiqi Liu

Dissertations

Drone-mounted base stations (DBSs) have emerged as a promising solution to enhance the flexibility and coverage of wireless networks, potentially revolutionizing communication systems. This dissertation explores the integration of DBSs into 5G and beyond networks, focusing on methodologies to optimize their deployment and performance. A laser charging-enabled DBS framework is proposed to extend flight time and enhance network coverage. By leveraging laser charging technology, the DBS can receive continuous energy transmission from a ground-based charging station while providing communication services to users. The framework is formulated as an optimization problem to jointly maximize flight time and communication data rate, while …

Computational Microscopy For Biomedical Imaging With Deep Learning Assisted Image Analysis, Yuwei Liu

Dissertations

Microscopy plays a crucial role across various scientific fields by enabling structural and functional imaging with microscopic resolution. In biomedicine, microscopy contributes to basic research and clinical diagnosis. Conventionally, optical microscopy derives its contrast from the amplitude of the optical wave and provides visualization of the physical structure of the sample qualitatively. To understand the function at the cellular or tissue level, there is a need to characterize the sample quantitatively and explore contrast mechanisms other than light intensity. Image enhancement or reconstruction from microscopic imaging systems is known as computational microscopy, and it involves the application of computational techniques …

Interaction Of Particles With Plasma And Shock Produced By Pulsed Spark Discharge, Shomik Mukhopadhyay

Dissertations

Interactions of powders with high-temperature plasma and shockwaves occur in diverse scenarios, such as nuclear blasts, accidental industrial dust explosions, solid propellant combustion in explosive charges and when removing contaminants from surfaces. Electrostatic Discharge (ESD), known for generating shock and plasma, is a promising lab-scale technique for simulating these interactions. Studies with ESD involved placing powders near a spark-producing gap between electrodes and observing mechanical and chemical processes like particle motion and ignition. A limited range of spark conditions and material properties have been tested, which facilitated the development and validation of preliminary computational models describing this system. Significant gaps …

Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell

Dissertations

In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …

Decentralized Control Of Renewable Generation Systems, Milad Shojaee

Dissertations

As the global community struggles with the escalating challenges of climate change and environmental degradation, the transition to renewable energy sources has emerged as a paramount solution. Harnessing energy from renewable sources such as solar, wind, and hydro power not only alleviates the adverse effects of conventional fossil fuel energy sources, but also establishes a foundation for a sustainable and resilient future. Microgrids have been utilized as a feasible platform to integrate renewable energy sources into the electrical power generation networks. They include one or more generation units connected to nearby users, and are able to operate in both grid-connected …

Information Theoretic Bounds For Capacity And Bayesian Risk, Ian Zieder

Dissertations

In this dissertation, the problem of finding lower error bounds on the minimum mean-squared error (MMSE) and the maximum capacity achieving distribution for a specific channel is addressed. Presented are two parts, a new lower bound on the MMSE and upper and lower bounds on the capacity achieving distribution for a Binomial noise channel. The new lower bound on the MMSE is achieved via use of the Poincare inequality. It is compared to the performance of the well known Ziv-Zakai error bound. The second part considers a binomial noise channel and is concerned with the properties of the capacity-achieving distribution. …

Sensing With Integrity: Responsible Sensor Systems In An Era Of Ai, David Eisenberg

Dissertations

Deep and machine learning now offer immense benefits for consumer choice, decision-making, medicine, mental health and education, smart cities, and intelligent transportation and driver safety. However, as communication and Internet technology further advances, these benefits have the potential to be outweighed by compromises to privacy, personal freedom, consumer trust, and discrimination. While ethical consequences for personal freedom and equity rise from these technological advances, the issue may not be the technology itself but a lack of regulation and policy that allow abuses to occur. A first study examines how emerging sensor-based technologies, limited to only accelerometer and gyroscope data from …

A Molecular Dynamics Study On The Destruction Mechanism Of Per And Polyfluoroalkyl Substances Due To Ultrasound Technology, Bruno Bezerra De Souza

Dissertations

Per- and polyfluoroalkyl substances (PFAS) are a group of stable synthetic chemicals that are highly persistent and harmful pollutants to the environment and human health. PFAS have caused a strong public and regulatory response due to their ubiquitous presence in the environment and toxicity to humans. The application of ultrasound is one of the most effective treatment technologies for the mineralization of PFAS in contaminated water. However, this technology is treated as a black box causing the inability to be optimized. Therefore, there is a pressing need to investigate the intricate dynamics of PFAS degradation under ultrasound to unlock its …

Molecular-To-Continuum Scale Modeling Of Aerosols: Atmospheric Application And Beyond, Ella Ivanova

Dissertations

Aerosol modeling is critical for various applications, such as climate forecasting, air quality, and human health impact assessment. During their lifetime, aerosols undergo a complex evolution, usually divided into several stages — formation, processing, transport, and removal — that occur on different scales. Thus, the choice of modeling methods depends on the stage considered. For example, certain stages of particle formation may require nano-scale modeling while aerosol-cloud interactions span from microscale to mesoscale. This study examines the modeling of aerosol behavior over a wide range of scales, from nano to microscale, with implications to mesoscale.

This dissertation focuses on two …

Microplastic Abundance And Removal In Stormwater Using Green Infrastructure, Meghana Parameswarappa Jayalakshmamma

Dissertations

Microplastics (MPs) are increasingly recognized as a pervasive environmental contaminant, conveying other contaminants, accumulating in aquatic organisms, and posing ecological risks. The existing research has primarily focused on MPs in wastewater treatment plant effluents in surface waters. However, the role of stormwater systems in MP transport has been less explored. Given the rise in MPs from urban sources, stormwater runoff from urban areas may serve as a critical conduit for transporting land-based MPs into aquatic environments. Green infrastructures (GIs) have been recognized for mitigating flooding and improving water quality from minor storms by trapping stormwater pollutants. Yet, the capability of …

A Machine Learning-Assisted Steering And Scheduling Framework For Big-Data Scientific Workflows On Heterogeneous Computing Platforms, Yijie Zhang

Dissertations

In next-generation scientific applications, the exponential growth of big data necessitates advanced techniques for efficient data storage, processing, and analysis. This has led to the construction of intricate computing workflows, managed and orchestrated by powerful engines in big data systems as exemplified by Hadoop. As scientific applications increasingly shift towards simulation-centric approaches, traditional methodologies face new challenges in accommodating the complexity of extreme-scale numerical modeling with numerous tunable parameters. To address these challenges, this dissertation propose to develop a machine learning-assisted framework that enables autonomous computational steering of scientific simulations and optimized execution of big-data workflows on heterogeneous platforms. This …

Reproducible Fluid Structure Interaction For Complex Flows In Engineered Systems, Allen Prasad Varghese

Dissertations

This dissertation focuses on the application of numerical models to study Fluid Structure Interaction (FSI) in the industrial context. The emphasis is on a series of case studies belonging to practical applications in design and manufacturing and that are solved by a synergistic use of theoretical and computational models. The first study looks into the hydrodynamic actions experienced by vibrating slender structures immersed in viscous fluids near the free surface. This study case is relevant to applications such as, for example, marine propulsion, micro-electro-mechanical systems, and atomic force microscopy. The hydrodynamic problem is governed by three parameters, namely the frequency, …

Development Of Super Hydrophobic Membranes And Their Applications, Sumona Paul

Dissertations

Effective liquid phase separation is vital across industries, especially in aviation, chemicals, fuels, and textiles. Membrane technology offers advantages over traditional methods like distillation, with low energy consumption and protection for heat-sensitive molecules. Membrane performance is assessed based on factors such as materials, surface modification, and interactions. This research targets superhydrophobic membranes for liquid-liquid filtration and antiwetting omniphobic membranes for membrane distillation, focusing on properties like contact angle and thermal resistance.

This study presents a highly hydrophobic membrane achieved by immobilizing carbon nanotubes (CNTs) onto a PTFE microfiltration membrane. It's designed for dewatering organic-water mixtures with trace water content via …

Neural Operator For Accelerating Coronal Magnetic Field Computations In Bifrost Mhd Model, Yutao Du

Theses

The application of the Tensorized Fourier Neural Operator (TFNO) to significantly enhance the computational efficiency of coronal magnetic field calculations within the Bifrost Magnetohydrodynamics (MHD) model is introduced in this study. Leveraging simulated data from the European Sunrise Science Data Center, the TFNO? an extension of the Fourier Neural Operator (FNO) that incorporates tensor decomposition for improved handling of high-dimensional data?is employed to solve time-varying partial differential equations (PDEs) over a 3D domain. The performance of the TFNO is compared with traditional machine learning methods, including Vision Transformer and CNN-RNN (encoder-decoder) architectures, to demonstrate its accuracy, computational efficiency, and scalability. …

Marking Estimation In Petri Nets Using Dynamic Mode Decomposition, Aditya Kale

Theses

Petri Nets (PNs) are a well-established framework for modeling and analyzing complex systems with interacting, concurrent processes. This thesis extends traditional Petri Net methodologies by integrating Dynamic Mode Decomposition (DMD), a technique originally developed for fluid dynamics, to analyze Continuous Petri Nets (CPNs). By applying DMD to CPN marking evolution, this research constructs a reduced-order model that captures its dynamics through dynamic modes and eigenvalues, enabling prediction of future markings without detailed knowledge of transition firings or underlying deterministic models. The principal contribution of this research is extending the kit of tools available for analysis of CPN dynamics, providing insights …

Effects Of Exoskeletal-Assisted Walking Rehabilitation On Gait Of Patients Post Stroke, Archisha Kanchan

Theses

Stroke can have detrimental effects on one's body. Its symptoms can range from lightheadedness to blurred vision to body paralysis. One of the more common effects of stroke is difficulty walking where many of the patients who have suffered from stroke are unable to ambulate fully. To mitigate gait difficulties, patients typically follow through with various kinds of physical therapy to help with their gait movements. Recently, robotic exoskeleton (RE) walking therapy has been used as a more innovative approach to gait rehabilitation, in conjunction with other physical therapy session techniques. However, studies involving RE therapy within the stroke population …

The Next Strike: Pioneering Forward-Thinking Attack Techniques With Rowhammer In Dram Technologies, Nakul Kochar

Theses

In the realm of DRAM technologies this study investigates RowHammer vulnerabilities in DDR4 DRAM memory across various manufacturers, employing advanced multi-sided fault injection techniques to impose attack strategies directly on physical memory rows. Our novel approach, diverging from traditional victim-focused methods, involves strategically allocating virtual memory rows to their physical counterparts for more potent attacks. These attacks, exploiting the inherent weaknesses in DRAM design, are capable of inducing bit flips in a controlled manner to undermine system integrity. We employed a strategy that compromised system integrity through a nuanced approach of targeting rows situated at a distance of two rows …

Targeted Drug Delivery: Investigating Protein Corona Behavior, Atharva Markale

Theses

Due to high specificity and less toxicity, nanoparticles have become promising for targeted drug delivery against cancer, although they face challenges when they enter the bloodstream, making their behavior unpredictable. The deposition of proteins on nanoparticles, the protein corona, changes their biosignature, affecting their circulation, drug release potency, targeting ability, and immunogenicity. The continuous exchange of protein layers on a nanoscale is complex to analyze.

Nanoparticle tracking analysis (NTA) is a method to characterize nanoparticles in blood plasma by combining principles of light scattering microscopy and Brownian motion. In this work, time-dependent experiments with plasma were conducted to analyze the …

Strawberry Nectar Preservation Through Innovative Techniques And Energy Evaluation For High-Pressure Processing, Caterina Scaioli

Theses

Strawberries are universally adored by people of all ages, owing to their richness in vitamins, nutrients, and antioxidants, offering myriad health benefits, including combating free radicals. However, despite their popularity, strawberry juices or nectars are not commonly found in markets due to their delicate structure, which makes them prone to rapid deterioration of their prized qualities and vibrant red color. In the food industry, preventing browning and nutrient deterioration are often the primary challenges faced when processing red juices. Traditional preservation methods, such as pasteurization, are inadequate in maintaining their freshness. The focus of this study is to explore alternative …

Methodology For Developing Biodegradable Polymer Blends And Composites For Agriculture, Fangzhong Xing

Theses

The use of polyethylene (PE) films to improve soil conditions and to increase crop yield has produced microplastics that are harmful to our ecosystem. The overall objective of this thesis is to develop an effective biodegradable polymer/composite to replace PE, and hence, to reduce microplastic pollution. The focus of this research is to develop a systematic protocol for assessing the suitability of the biodegradable films based on industry standards in agriculture. For this purpose, a range of biodegradable polymer blends are prepared using polylactic acid (PLA) and polybutylene adipate-co-terephthalate (PBAT) with varying PLA to PBAT ratios. Solvent casting combined with …

Optimizing Social Determinant Of Health Concept Extraction, Niharika Singh

Theses

Generative Artificial Intelligence has recently garnered enormous attention for a varied number of reasons, one of them being its capacity to automate complex tasks. As the potential for integrating Generative Artificial Intelligence across technology, media, and healthcare grows, many tasks previously reliant on manual or algorithm-intensive methods can be simplified significantly. One such challenge is concept extraction, which is a labor-intensive process, especially when performed manually for building robust ontologies. It involves analyzing text to identify and extract relevant concepts, key phrases, entities, and relationships between these entities. This thesis explores various challenges of concept extraction from the ABCD (Adolescent …

Electrochemical Nitrate Reduction To Ammonia On Cu Based Nanoparticles Using Quantum Mechanical Simulations, Kathan Bhavin Shukla

Theses

Nitrate reduction to ammonia (NRA) is critical for environmental remediation and energy conservation, as it can remove harmful nitrate (NO₃^-) from water sources while producing usable ammonia (NH₃). Cu represents one of the most promising non-noble-metal NRA electrocatalysts. However, the intrinsic catalytic activity of Cu facets and their influence under different pH conditions remain unclear, particularly in the presence of ions commonly found in wastewater such as Cl^-, Na⁺, Mg²⁺, and Ca²⁺. Using density functional theory (DFT) calculations, we evaluated the nitrate reduction to ammonia (NRA) pathways …

Trans-Disciplinary Communication For Policy Making: A Reflective Activity Study, Cristo Leon

STEM for Success Resources

This paper reports on a workshop conducted at the NSF's 2023 Eddie Bernice Johnson, INCLUDES National Network Convening: Sustaining Equity-Driven Systems Change, held in Washington, DC, from August 2-4, 2023. Titled "Enhancing Inclusivity through Expertise Sharing: A Reflective Group Activity on Effective Policy Development," the workshop employed Trans-Disciplinary Communication (TDC) as a methodological framework. Participants represented a cross-section of academia, nonprofits, federal agencies, and the general public, focusing on STEM Education, diversity, equity, and inclusion (DEI), and traditionally underrepresented groups (TUG). The paper delineates the protocol for eliciting robust participation and facilitating knowledge sharing. Subsequently, it scrutinizes the outcomes of …

Analyzing The Meta Dimensions In Trpgs: Meta-Action, Metacognition, And Metagaming, Cristo Leon, James Lipuma

STEM for Success Resources

Roleplay has critically influenced academic dialogue on education, psychology, and narrative. However, little research has been conducted around "gaming sessions," specifically the "point of contact" amongst participants, due to its ephemeral qualities and the subjective nature of the co-creative process. Acknowledging the complexity of the subject, the authors established a clear set of definitions. They conducted a literature review to examine the existing understanding of critical components related to gameplay in Tabletop Roleplay Games (TRPGs). They are exploring TRPGs through the lens of narrative storytelling to understand better and categorize the 'collaborative' and 'co-designed interactions during the gameplay experience. The …

Using Trans-Disciplinary Communication In The Design Of General Education Program Assessment: A Case Study, Jeremy P. Reich, James Lipuma, Cristo E. Yáñez León

STEM for Success Resources

No abstract provided.

Trans-Disciplinary Communication In Collaborative Co-Design For Knowledge Sharing, James Lipuma, Cristo Leon

STEM for Success Resources

Journal of Systemics, Cybernetics and Informatics.
© All rights reserved. Systemics, Cybernetics, and Informatics, 2024

https://www.iiisci.org/DOIJSCI/SA218XL23/

Research Experiences For Students At Njit & Nsf April 2024, Cristo Leon

STEM for Success Resources

Presentation for NJIT students